Real-time track reconstruction in high-energy physics experiments at colliders running at high luminosity is very challenging for trigger systems. To perform pattern recognition and track fitting, artificial retina or...Real-time track reconstruction in high-energy physics experiments at colliders running at high luminosity is very challenging for trigger systems. To perform pattern recognition and track fitting, artificial retina or Hough transformation algorithms have been introduced to the field typically implemented on state-of-the-art field programmable gate array(FPGA) devices. In this paper, we report on two FPGA implementations of the retina algorithm: one using a mixed Floating-Point core and the other using Fixed-Point and Look-Up Table, and detailed measurements of the retina performance are investigated and compared. So far, the retina has mainly been used in a detector configuration comprising parallel planes, and the goal of our work is to study the hardware implementation of the retina algorithm and estimate the possibility of using such a method in a real experiment.展开更多
基金supported by the National Key Research and Development Program of China(No.2016YFE0100900)Fundamental Research Funds for the central universities(No.2018YBZZ082)+1 种基金National Science Funds of China(No.11505074)Belgian FRS-FNRS
文摘Real-time track reconstruction in high-energy physics experiments at colliders running at high luminosity is very challenging for trigger systems. To perform pattern recognition and track fitting, artificial retina or Hough transformation algorithms have been introduced to the field typically implemented on state-of-the-art field programmable gate array(FPGA) devices. In this paper, we report on two FPGA implementations of the retina algorithm: one using a mixed Floating-Point core and the other using Fixed-Point and Look-Up Table, and detailed measurements of the retina performance are investigated and compared. So far, the retina has mainly been used in a detector configuration comprising parallel planes, and the goal of our work is to study the hardware implementation of the retina algorithm and estimate the possibility of using such a method in a real experiment.
